Avinashilingam University

In hilly and mountainous areas, landslides are among the most destructive natural disasters, particularly during periods of intense precipitation. Human lives,transportation networks, and infrastructure are all severely harmed by sudden slope failures. Conventional monitoring systems are not appropriate for remote locations since they are frequently manual, costly, and do not have real-time alert capabilities. A LoRa-based Internet of Things landslide detection and early warning system is proposed in this paper for ongoing slopemonitoring and prompt risk assessment. Numerous sensors are integrated into the system, such as the DHT11 for environmental monitoring, the soil moisture sensor, the vibration sensor, and the MPU6050 for tilt and acceleration. The sensor data is processed by an ESP32microcontroller and sent to a monitoring station via LoRa communication. LEDs and a buzzer are used to create local alerts, and data is sent to a cloud dashboard foroversight from a distance. For deployment in areas vulnerable to landslides, the suggested system provides long-range communication, low power consumption, dependability, and affordability. Keywords: early warning system, disaster management, IoT, LoRa communication, and landslide detection.

Abstract The increasing incidents of crop damage and human–wildlife conflict near agrarian and forest boundary areas highlight the need for intelligent and robotic protection systems. Traditional fencing methods often fail to provide real-time monitoring and may harm animals or require constant human supervision. This study presents the design and implementation of a Smart Forest Fencing System, an AI-driven surveillance solution that enhances farm security using computer vision and deep learning techniques. The proposed system monitors farm boundaries using cameras and employs the YOLOv8 deep learning model to detect and classify animals into wild or domestic categories. Based on the classification results, the system automatically triggers appropriate responses such as alerts, visual deterrents, and instant notifications to farmers via SMS or email. By integrating image processing, automated alerts, and intelligent decision-making, the proposed system enhances monitoring effectiveness, reduces crop damage, and promotes a safe and non-lethal approach to wildlife management. Keywords: Smart Fencing System, YOLOv8, Object Detection, Wildlife Monitoring, AI-Based Surveillance, Farm Security, Real-Time Monitoring, Animal Classification

Indigenous communities have unique traditional food systems. The traditional Khasi and Jaintia plates consist of both raw and cooked food items. Locally sourced herbs, tubers and plants are common in their food habits. Mustard greens, Indian pennywort, garlic chives, fish mint, turmeric tuber, chayote, ginger and garlic are some of the commonly used plant foods among these tribes. This study aimed to evaluate the relationship between the consumption of indigenous superfoods and immunocompetence measured through micronutrient biomarkers. Informed consent and ethical clearance were obtained before the study. A web-based tool was constructed with sociodemographic information and a quantitative food frequency questionnaire on indigenous food consumption patterns. The 24-hour dietary recall was used to assess nutrient intake. The blood samples were estimated for SARS-CoV antibody levels and serum levels of vitamin C, zinc and selenium. A total of 553 participants completed the questionnaire. Less than ten percent of the study population had COVID-19. The asymptomatic presentation among the study population was predominant even after the pandemic. Greater intake of macronutrients such as carbohydrates, protein and fats was observed (p<0.05) in the study participants, with increased dietary intake of immunonutrients such as selenium and vitamin B6 (p<0.05). The presence of SARS-CoV-2 antibodies indicated that all the patients were infected, yet the asymptomatic nature of the disease prevailed in 87.7% of the population. The indigenous foods ginger (Zingiber officinale) (p=0.032), garlic (Allium sativum) (p=0.023), turmeric tuber (Curcuma longa) (p=0.036), mustard leaves (Brassica juncea) (p=0.021) and dietary selenium intake (p=0.040) were positively associated with the serum levels of the micronutrients vitamin C and zinc. The indigenous foods ginger, turmeric tuber, and mustard leaves, along with high intakes of dietary sources of selenium and B6, have had a protective effect and have led to the asymptomatic presentation of COVID-19 infection in this tribal population.

Capital markets' derivative markets have recently experienced stronger growth. In recent years, the financial markets derivative sector has grown more quickly. Investors' attention is shifting away from the stock market and towards the futures market. Individual investors are becoming more active in the derivatives market. While trading, psychological factors will lead investors to make impulsive and emotional judgements. This study tracks how attitude, personality traits and behavioural biases shape their investment intention and analyses the moderating role of financial literacy and self-efficacy on the derivative market. Snowball technique was adopted to collect the primary data from 125 investors from Coimbatore city. Mean and standard deviation, Kruskal Wallis test and structural equational model were used for analysing the collected data. The study concluded that attitude, personality traits and behavioural biases significantly influence investment intention and the moderating effect of financial literacy is more than self-efficacy.

Histidine phosphotransfer proteins (HP/Hpts) are key components in the two-component system (TCS) involved in cytokinin signalling. In rice, five Hpt genes have been identified, including two authentic and three pseudo-Hpts. This study focused on isolating and characterizing the OsHpt4/PHP2-like gene from three O. indica rice varieties, and on exploring the evolutionary and regulatory features of the Hpt gene family across Oryza species. Hence, we isolated the OsHpt4/PHP2-like gene (456bp; 151 amino acids) from three O. indica rice varieties- ASD-16 (Parentage- ADT 31/Co39), ADT-54 (Parentage-I.W.Ponni/ Banskathi) and CO-52 (Parentage- BPT 5204/ Co (R) 50) and compared their physicochemical properties. To gain broader insights, a genome-wide analysis was conducted across six Oryza species (Oryza sativa ssp. japonica, Oryza sativa ssp. indica, Oryza rufipogon, Oryza nivara, Oryza glumaepatula, and Oryza barthii), identifying 35 Hpt isoforms. Studies on gene structure and conserved motifs showed that intron and exon organization, as well as motif composition, are well preserved. Phylogenetic analysis grouped Hpts into four main clusters with other monocots. Both segmental and tandem gene duplications contributed to gene family expansion. Promoter analysis revealed cis-elements responsive to phytohormones, abiotic stresses, light, and development. These results offer new insights into the evolution and regulation of Hpt genes in rice, and it paves a strong avenue for future research on stress tolerance and crop improvement.

<title>Abstract</title> Breast cancer is a leading cause of cancer morbidity and mortality globally, with numerous environmental and genetic factors contributing to its progression. Among environmental factors, exposure to endocrine-disrupting pesticides (EDPs) has garnered significant attention due to their ability to interfere with hormonal pathways, particularly those involving estrogen signalling. This study investigates the molecular docking interactions of widely used pesticides with estrogen receptors ERα, ERβ, and GPER to elucidate their potential role as an endocrine-disrupting pesticide (EDP) in breast cancer. Cyahlothrin is widely used synthetic pyrethroid pesticides among others.The docking analysis revealed strong binding affinities of Cyhalothrin with ERα (-8.6 kcal/mol), ERβ (-11.0 kcal/mol), and GPER (-11.8 kcal/mol). Compared to other EDPs, the results show that Cyhalothrin exhibits superior receptor-binding properties, emphasizing its role as a potent disruptor of estrogenic pathways. These findings suggest that Cyhalothrin mimics endogenous estrogens, leading to overactivation of ERα, suppression of ERβ, and activation of GPER, disrupting normal estrogen signalling. Understanding the molecular interactions between cyhalothrin and estrogen receptors is crucial for assessing its potential role in breast cancer progression. The study also underlines the critical need for stringent regulatory measures to mitigate exposure to Cyhalothrin and similar pesticides to reduce their impact on breast cancer risk. Furthermore, molecular dynamics simulations confirmed the stability of the Cyhalothrin–ERα complex, while Swiss ADME and ADMET-AI analyses revealed favourable drug-like properties but significant carcinogenic and hepatotoxic tendencies. Swiss Target Prediction, ProTox-3.0, and endocrine-disruption screening through ToxCast/Tox21 validated Cyhalothrin’s interaction with estrogenic and oncogenic pathways, reinforcing its classification as a potent endocrine-disrupting pesticide in breast cancer.